netflix_data <- read_csv("netflix-rotten-tomatoes-metacritic-imdb.csv")

-- Column specification -----------------------------------------------------------------------------------------------
cols(
  .default = col_character(),
  `Hidden Gem Score` = col_double(),
  `IMDb Score` = col_double(),
  `Rotten Tomatoes Score` = col_double(),
  `Metacritic Score` = col_double(),
  `Awards Received` = col_double(),
  `Awards Nominated For` = col_double(),
  `Netflix Release Date` = col_date(format = ""),
  `IMDb Votes` = col_double()
)
i Use `spec()` for the full column specifications.
netflix_data_cleaned <- read_csv("netflix-rotten-tomatoes-metacritic-imdb.csv")

-- Column specification -----------------------------------------------------------------------------------------------
cols(
  .default = col_character(),
  `Hidden Gem Score` = col_double(),
  `IMDb Score` = col_double(),
  `Rotten Tomatoes Score` = col_double(),
  `Metacritic Score` = col_double(),
  `Awards Received` = col_double(),
  `Awards Nominated For` = col_double(),
  `Netflix Release Date` = col_date(format = ""),
  `IMDb Votes` = col_double()
)
i Use `spec()` for the full column specifications.
netflix_data$Image[5]
[1] "https://occ-0-4039-1500.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABb72YCHDSHzrB8i5_iG56UFm-qV2bslRyMHIqZ4tmlIpeVtMsqAyUem6JAxXtV4Ec9jlA4EpTdf5tNX2ivyLUwmPy4d3xowFdJE63MPXbWu8kAnc-j9qhAZrmMI.jpg?r=fad"
names(netflix_genre)
[1] "netflix_data$Genre"
netflix_data %>%
  filter(grepl(head(netflix_actors, n = 1), Actors))
fig
No scattermapbox mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
No scattermapbox mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
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